A flexible image database system for content-based retrieval

被引:51
作者
Berman, AP [1 ]
Shapiro, LG [1 ]
机构
[1] Univ Washington, Dept Comp Sci & Engn, Seattle, WA 98195 USA
基金
美国国家科学基金会;
关键词
D O I
10.1006/cviu.1999.0772
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There is a growing need for the ability to query image databases based on similarity of image content rather than strict keyword search. As distance computations can be expensive, there is a need for indexing systems and algorithms that can eliminate candidate images without performing distance calculations. As user needs may change from session to session, there is also a need for run-time creation of distance measures. In this paper, we present FIDS, "flexible image database system." FIDS allows the user to query the database based on complex combinations of dozens of predefined distance measures. Using an indexing scheme and algorithms based on the triangle inequality, FIDS can often return matches to the query image without directly comparing the query image to more than a small percentage of the database. This paper describes the technical contributions of the FIDS approach to content-based image retrieval. (C) 1999 Academic Press.
引用
收藏
页码:175 / 195
页数:21
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